- Annual Meeting
Pre-meeting workshops are held on Wednesday, October 3 for an additional fee. Please review the details below.
Pre-Meeting Workshop #1
Event-related potentials (ERPs) are one of the most commonly used noninvasive measures of human brain activity. This workshop will provide a practical introduction to using ERPs to answer questions about sensory, cognitive, affective, and motor processes in basic science and clinical research. The goal of the workshop is to provide you with a sufficiently detailed overview so that you can fully understand and evaluate published ERP studies and start on the road to conducting your own ERP studies. It is designed for beginning and intermediate ERP researchers—at any career stage—who would like to obtain a firm grasp of the fundamentals of ERP research.
Pre-Meeting Workshop #2
Multilevel modeling (MLM) is a statistical analysis used to analyze datasets where cases are not independent (e.g., repeated measures), as is commonly the format in which psychophysiological data is recorded. Moreover, MLM is a flexible analysis that can be learned once and readily adapted to most psychophysiological designs. Especially for psychophysiologists who are used to working with Within-Subjects ANOVA, MLM offers an improved method for harnessing the statistical power of within-subjects designs and can easily incorporate continuous predictors. This workshop will provide a practical introduction to MLM for psychophysiologists, including advanced topics like growth curves, non-Gaussian data, cross-classified models, mediation, moderation, and the calculation of effect sizes. Workshop materials will include example data and syntax for SPSS, R, and SAS. The goal is for you to leave the workshop with the conceptual and pragmatic knowledge you need to immediately begin analyzing psychophysiological data with MLM.
Outline of Workshop:
1. Effect Size and Power with MLM
Conclusion and Recommendations
Pre-Meeting Workshop #3
Neuroimaging methods such as fMRI, MEG or EEG are useful for studying brain function non-invasively. Recently, they have been increasingly used in conjunction with complex stimuli such as natural images, video, speech or texts. We will cover in this workshop the encoding and decoding approaches that are commonly used to analyze the brain activity evoked by complex stimuli. Encoding models are predictive models that learn the relationship between stimulus properties and brain activity, whereas decoding refers to identifying the stimulus from brain activity. Through this workshop, you will learn how to build feature spaces that describe different types of stimulus properties, and how to use these features spaces to fit an encoding model that predicts brain activity. You will also learn how to use this encoding model to build a brain decoder. The goal of the workshop is to teach you the entire pipeline of building encoding models, and how to use these models to make inferences about what is being represented in different brain areas. We will focus on experiments that study language representations but the methodology is easily generalizable to other cognitive modalities.
Outline of Workshop:
• Introduction to different imaging modalities and neuroimaging paradigms